Anterior cruciate ligament (ACL) injury continues to be at the forefront of sports injury concerns because of its impact on quality of life and joint health prognosis. One strategy is to reduce the occurrence of this injury by identifying at-risk subjects based on key putative risk factors. The purpose of our study was to develop models that predict the structural properties of a subject's ACL based on the combination of known risk factors. We hypothesized that the structural properties of the ACL can be predicted using a multi-linear regression model based on significant covariates that are associated with increased risk of injury, including age, sex, body size, and ACL size. We also hypothesized that ACL size is a significant contributor to the model. The developed models had predictive capabilities for the structural properties of the ACL: load at failure (R2 = 0.914), elongation at failure (R2 = 0.872), energy at failure (R2 = 0.913), and linear stiffness (R2 = 0.756). Furthermore, sex, age, body mass, BMI, and height were contributors (p < 0.05) to all predicted structural properties. ACL minimal area was a contributor to elongation, energy at failure, and linear stiffness (p < 0.05), but not to load at failure. ACL volume was also a contributor to elongation and energy at failure (p < 0.05), but not to linear stiffness and load at failure models. ACL length was not a significant contributor to any structural property. The clinical significance of this research is its potential, after continued development and refinement of the model, for application to prognostic studies that are designed to identify individuals at increased risk for injury to the ligament.
Copyright © 2011 Orthopaedic Research Society.